Bjarne Ørum Fruergaard

As an
Industrial PhD working with Adform (www.adform.com), my research
involves investigation and development of new models for predictive
targeting in online display advertising based on statistical
learning. Our main hypothesis is that the actions a user performs
when navigating and interacting with web sites (clicks, page
visits, previous conversions,etc.) reveal weak
signals which can be used to infer user behavior and
goals.

The
rarity of user actions poses a challenge for ordinary collaborative
filtering (CF) techniques; hence I investigate augmenting CF with
side-information about the users and how that can be used for
inferring user similarity and thus improve the predictive
performance in cold-start settings.

The
dynamics of online user behavior is another area of research.
Adform’s role as a key international digital advertisement
platform, offers unique possibilities for closed-loop experiments.
I.e., my research entails investigating active learning
strategies to reduce uncertainties of model parameters in the face
of data in which our algorithms have been used to decide on test
candidates (banners).